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This paper examines the hypothesis of local herding (i.e. own-area effects) by individual investors on a particular stock-month. Using a unique dataset on online and offline individual investors’ trading records in Korea, we analyze buying and selling transactions involving 10,000 accounts from February 1999 to December 2005. We find that both online and offline investors in the same area tend to exhibit stronger local herding compared to investors’ trades who are geographically remote. Interestingly, online investors not only present stronger own-area effects but also exhibit more pronounced other-area effects compared with offline investors. Furthermore, our analysis indicates that gender and religious affiliation are important in investment behavior, with male and non-religious investors displaying a greater stock market participation in contrast to investors who are female and Protestant.

To achieve sustainable development in shipping, accurately identifying the impact of artificial intelligence on shipping carbon emissions and predicting these emissions is of utmost importance.

A multivariable discrete grey prediction model (WFTDGM) based on weakening buffering operator is established. Furthermore, the optimal nonlinear parameters are determined by Grey Wolf optimization algorithm to improve the prediction performance, enhancing the model’s predictive performance. Subsequently, global data on artificial intelligence and shipping carbon emissions are employed to validate the effectiveness of our new model and chosen algorithm.

To demonstrate the applicability and robustness of the new model in predicting marine shipping carbon emissions, the new model is used to forecast global marine shipping carbon emissions. Additionally, a comparative analysis is conducted with five other models. The empirical findings indicate that the WFTDGM (1, N) model outperforms other comparative models in overall efficacy, with MAPE for both the training and test sets being less than 4%, specifically at 0.299% and 3.489% respectively. Furthermore, the out-of-sample forecasting results suggest an upward trajectory in global shipping carbon emissions over the subsequent four years. Currently, the application of artificial intelligence in mitigating shipping-related carbon emissions has not achieved the desired inhibitory impact.

This research not only deepens understanding of the mechanisms through which artificial intelligence influences shipping carbon emissions but also provides a scientific basis for developing effective emission reduction strategies in the shipping industry, thereby contributing significantly to green shipping and global carbon reduction efforts.

The multi-variable discrete grey prediction model developed in this paper effectively mitigates abnormal fluctuations in time series, serving as a valuable reference for promoting global green and low-carbon transitions and sustainable economic development. Furthermore, based on the findings of this paper, a grey prediction model with even higher predictive performance can be constructed by integrating it with other algorithms.

Grounded in social cognitive career theory, this study investigates how employees' perceptions of job security and well-being affected their performance during the COVID-19 pandemic. It also examines the moderating effects of perceived organizational support and psychological capital on well-being and performance.

Using a two-wave time-lagged design, data were collected from 279 frontline employees in public service organizations in Saudi Arabia.

The study’s results show that perceived job security significantly affects job performance. Employee well-being significantly and positively influences job performance and partially mediates the relationship between perceived job security and job performance. Additionally, perceived organizational support and psychological capital positively moderated the relationship between employee well-being and job performance during the pandemic.

This study suggests that policymakers and practitioners need to prioritize addressing the job security concerns and well-being of frontline employees during a pandemic to enhance employee performance.

Our findings present significant implications for policymakers in the context of job security and performance within public organizations in emerging countries.

本研究以社會認知生涯理論為基礎,去探討在2019冠狀病毒病疫情期間,僱員對職業保障和福祉的看法如何影響他們的工作績效; 研究亦擬探討感知組織支持和心理資本對福祉和工作績效所起的調節作用。

研究人員使用雙波時間遞延設計收集數據; 數據取自於沙特阿拉伯的公共服務組織內工作的279名一線員工。

研究結果顯示,僱員的感知職業保障會對他們的工作績效有顯著的影響; 另外,僱員的福祉會正面和顯著地影響他們的工作績效; 而且,僱員的福祉也會局部地調節感知職業保障與工作績效之間的關係。再者,研究人員發現,在大流行期間,感知組織支持和心理資本正面調節了僱員福祉與工作績效之間的關係。

研究結果建議政策制定者和從業人員必須於大流行肆虐期間,優先處理有關職業保障的關注和一線員工的福祉,俾能提升僱員的工作績效。

本研究的結果為政策制定者提供了重要的啟示,幫助他們於公共組織的環境內,能更有效地處理關於職業保障和僱員工作績效的事宜。

The purpose of the paper is to examine the effect of chief executive officer (CEO) succession on environmental, social and governance (ESG) performance and whether the characteristics of the incoming CEO, in terms of both gender and career horizon, are able to affect the relationship between CEO succession and ESG score.

The paper investigates a sample of European-listed companies between 2010 and 2021. Difference-in-difference and fixed-effects regressions are employed as the base empirical methodology. In addition, the robustness of the empirical findings is assessed by employing alternative methodologies and a different ESG proxy.

The empirical findings show the existence of a positive link between CEO succession and ESG performance and that this relationship is affected by two characteristics of the incoming CEO. Specifically, the empirical evidence indicates that the positive effect is magnified by the gender and the career horizon of the incoming CEO.

Considering the lack of research, this paper is the first one that opens a debate about the effects of CEO succession on corporate ESG performance in several European countries. By employing a unique sample of European listed firms, which has never been examined in other empirical research, this study highlights the importance of the demographic features of the incoming CEOs that should be taken into consideration during their selection process.

Literature on the board diversity of Islamic banks (IB) found limited knowledge of the “deep-level” attribute. This study aims to explain the impact of the board diversity attributes (education levels, educational backgrounds and the interactions between these two attributes of diversity) on profitability.

The research sample is 37 fully flagged IBs from five Southeast Asian countries, covering nine years (2010–2019). Data were analyzed using the two-step system generalized moment (2SYS-GMM) method.

We found that the cognitive conflict between the board of directors (BOD) and the Shariah Supervisory Board (SSB), which has heterogeneity in its education level and educational background, positively affects profitability. These results reinforce the resources dependence theory (RDT) approach that having boards with heterogeneous characteristics is beneficial for IB.

The findings of this study would offer useful information for Islamic banking authorities to revise or formulate rules and guidelines and make a greater effort to implement corporate governance (CG) reform measures by determining educational level and background as a requirement to become a member of a BOD or an SSB.

This paper contributes in three ways: (1) we use the “deep-level” diversity attributes of the BOD and the SSB, (2) it focuses on cognitive conflict in boards by presenting the expertise diversity of the BOD and SSB and (3) we interact with the level of education to evaluate the effect of a cognitive conflict.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.

Passive investing has established itself as the dominant force in the world of professionally managed assets, surpassing the concept of index funds. Its meteoric rise is fueled by investors’ preference for its dual benefits of strong diversification and low cost. A comprehensive study of the economic model, addressed areas and market structure has not yet been conducted, despite the existence of numerous studies on more specific topics. To address this gap, this paper examines 943 articles on passive investing published between 1998 and 2022 in SCOPUS and Web of Science.

The study utilizes the most pertinent tools for conducting a systematic review by the PRISMA framework. This article is the result of SLR and extensive bibliometric analysis. Contextualized systematic literature review is used to screen and select bibliographic data, which is then subjected to a variety of bibliometric analyses. The study provides a bibliometric overview of works on passive investment research that are indexed in Scopus and Web of Science. Bibliometrix, VoS Viewer and Cite Space are the tools used to conduct content and network analysis, to ascertain the present state of research, as well as its focus and direction.

Our exhaustive analysis yields important findings. One, the previous decade has witnessed a substantial increase in the number of publications and citations; in particular, the inter-disciplinary and international scope of related research has expanded; Second, the top three clusters on “active versus passive funds,” “price discovery and market structures” and “exchange-traded funds (ETFs) as an alternative” account for more than fifty percent of the domain’s knowledge; Third, “Leveraged ETFs (LETFs)” and “environmental, social and governance (ESG)” are the two emerging themes in the passive investing research. Fourth, despite its many benefits, passive investing is not suitable for everyone. To get the most out of what passive investing has to offer, investors, intermediaries and regulators must all exercise sufficient caution. Our study makes a substantial contribution to the field by conducting a comprehensive bibliometric analysis of the existing literature, highlighting key findings and implications, as well as future research directions.

While the study contributes significantly to the field of knowledge, it has several limitations that must be considered when interpreting its findings and implications. With our emphasis on academic journals, the study analyzed only peer-reviewed journal articles, excluding conference papers, reports and technical articles. While we are confident that our approach resulted in a comprehensive and representative database, our reliance on Elsevier Scopus and Web of Science may have resulted in us overlooking relevant work accessible only through other databases. Additionally, specific bibliometric properties may not be time-stable, and certain common distribution patterns of the passive investing literature may still be developing.

With this study, it has been possible to observe and chart the high growth trajectory of passive investing research globally, especially post-US subprime crisis. Despite the widespread adoption of passive investing as an investment strategy, it is not a one-size-fits-all proposition. Market conditions change constantly, and it frequently requires an informed eye to determine when and how much to shift away from active investments and toward passive ones. Currency ETFs enable investors to implement a carry trade strategy in their portfolios; however, as a word of caution, currency stability and liquidity can play a significant role in international ETFs. Similarly, LETFs may be better suited for dynamic strategies and offer less value to a long-term investor. Lastly, the importance of investor education cannot be underestimated in the name of the highly diversified portfolio when using passive alternatives, for which necessary efforts are required by regulators and investors alike.

The inexorable trend to passive investing creates numerous issues for fund management, including fee and revenue pressure, which forces traditional managers to seek new revenue streams, such as illiquid and private assets, which also implies increased portfolio risk. Additionally, the increased transparency and efficiency associated with the ETF market indicates that managers must rethink the entire value chain, beginning with technology and the way investments interact. Passive investments have triggered changes in market structure that are still not fully understood or factored in. Active management and a range of valuation opinions on whether a price is “too low” or “too high” provide much-needed depth to a market as it attempts to strike a delicate balance between demand and supply forces, ensuring liquidity at all price points.

I hereby certify that I am the sole author of this paper and that no part of this manuscript has been published or submitted for publication.

The purpose of this paper is to examine career engagement and perceived employability during the school-to-work transition. We studied within-person changes in career engagement and perceived employability in the transition from higher education to the labor market. We investigated their dynamic reciprocal relationship to unravel whether career engagement or perceived employability is the leading indicator in the relationship in view of providing adequate support for students during the school-to-work transition.

We conducted latent change score (LCS) analyses on a three-wave sample of 701 graduates in Flanders (Belgium). We collected data in July (right before graduation), November and May. LCS is a novel method allowing to simultaneously test change and reciprocal relationships.

Our findings demonstrated how both career engagement and perceived employability changed (within-person) non-linearly during the school-to-work transition. As for their relationship, we found that perceived employability is the driving force in the relationship. Perceived employability fueled subsequent positive changes in career engagement, whereas career engagement did not lead to subsequent changes in perceived employability.

Our study connects the career development and the graduate employability literature, and examines the school-to-work transition from preparation for the labor market to ten months after graduation. We also make an important methodological contribution, demonstrating the added value of LCS for studying employability in higher education. Our findings provide insights in how higher education institutions may support students in the school-to-work transition.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

We develop a credit-risk model to study the informational role of investment in an economy susceptible to large liquidity shocks. Firms' investment decisions carry information about their asset quality, thereby mitigating informational frictions when firms enter bankruptcy. An increase in aggregate investment can reduce the informational value of investment, depressing firms' recovery values. Therefore, policies boosting investment can decrease debt and firm values by reducing the informational value of investment. The presence of debt overhang may enhance firm value by making firms' investment decisions more informative. We present suggestive empirical evidence consistent with model predictions on the relation between firms' investments and recovery rates.